Mobile advertising is widely used by advertisers to market their products via mobile devices. Given the widespread availability of mobile devices, mobile advertising can be an extremely effective way for advertisers to reach a wide mass of potential customers and induce numerous users to purchase their products. By targeting mobile users with effective mobile advertisements, advertisers can yield large financial returns from their mobile advertisements. Not surprisingly, many advertisers continuously measure the performance of their advertisements to understand how, if necessary, they can optimize their advertisements for a better performance.
Many metrics are currently available for advertisers to measure the performance of their advertisements. For example, advertisers can measure the ratio of conversions obtained through their advertisements. In addition, advertisers can typically measure the number of views of a particular advertisement, to estimate the number of users reached by the particular advertisement and advertisement medium used. Unfortunately, however, it is generally difficult for advertisers to compare different advertisements based on the number of views measured, particularly when the different advertisements have varying amounts of content. Moreover, advertisers are currently unable to accurately and effectively determine the user's time spent engaging in an advertisement, and thus are limited in their understanding of the effects and performance of their advertisements.
Yet the user's time spent engaging in an advertisement can vary significantly, particularly in the mobile context. For example, mobile users frequently use their mobile device while engaging in other activities. Thus, mobile users are often distracted or disengaged at some point during their mobile session. And advertisers, on the other hand, are unable to determine the user's time spent engaged in the advertisement, or even whether the user was distracted or disengaged during any part of the advertisement. Consequently, advertisers are greatly limited in their ability to optimize their advertisements. Moreover, without accurate information regarding the user's engagement in an advertisement, it is very difficult to prevent click fraud from publishers seeking to inflate the metrics for their applications without actually showing the advertisements to real users.